International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

The rapid integration of generative artificial intelligence (Generative AI) tools into higher education has significantly influenced student learning behaviour and academic practices. This research paper explores the ways in which undergraduate students at Sofia University “St. Kliment Ohridski” apply these technologies for both academic and non-academic purposes. The results reveal that students predominantly use Generative AI for academic support, such as explaining complex concepts, conducting research, and assisting in writing tasks. At the same time, they also engage with Generative AI for personal productivity, communication, and creative exploration. Despite having generally positive perceptions of academic effectiveness, students show critical awareness of risks related to information accuracy, privacy, and ethical use.

Data analysis, particularly predictive analysis, has seen significant development with the emergence of modern LLMs,
especially the latest GPT models. Nowadays, Generative AI is a turning point in modern industry. Many new LLMs have been available
during the last several years, but an essential case is how these models are changing: what is the direction of evolution, and what can we
expect from Gen AI shortly?
This study analyses different aspects of the evolution of predictive analysis systems using different LLMs: GPT 3.5 turbo, GPT-4, GPT-
4o, GPT-4o1 OpenAI GPT o1.
This report includes comparative studies of predictive analysis for construction structures conducted using a comparative reference
framework with different GPT models, reaching GPT-4o and GPT o1. The accuracy of the analysis on identical cases is compared. The
study also compares the cost and performance of the different models. Current research will be useful for scientists, researchers, industry
engineers, and businesses to estimate the cost and effectiveness of the GenAI solutions that they are going to implement and choose the right
LLM for their cases and

Nowadays, many structures should be inspected, analyzed, and repaired. This is a complex and expensive process that also includes predictive analytics to prevent possible construction failures.
One of the most used predictive analytics applications involves extracting necessary metadata from images and videos to evaluate the condition of real-world systems and recommend measures to sustain these systems. Image analysis is not a new concept – many solutions have been used for several decades.
The current paper mainly focuses on OpenAI-based capabilities to implement Image Analysis and Cognitive Digital Twins and proposes faster, cheaper implementation and more adaptive approaches to offering predictive analysis for constructions.
ChatGPT (Chat Generative Pre-Trained Transformer) is one of the trending technologies in modern Artificial Intelligence (AI), and experts in this area expect to have a very high impact on the industry shortly.
One of the latest versions – GPT-4 Turbo with Vision, developed by OpenAI, is a significant multimodal model (LMM) capable of interpreting images and providing text-based answers to queries regarding those images. It combines capabilities in natural language processing and visual comprehension.
The proposed approach considers using OpenAI LLM and Digital Twins for three different aspects of predictive analysis for Construction: image analysis, case decomposition, and creation of self-adaptive models to find possible trends to compromise structures and offer preventive actions. This research compares traditional methods for inspection and repair of Construction, including the time required for predictive analysis, the correctness of the proposed actions, and the cost of the methodology.

Generative AI models have started to transform the software industry, driving innovation, and automating tasks previously deemed complex. This overview delves into the evolution, applications, and potential of these models, highlighting their capability to create novel content, enhance software development processes, and forecast industry trends. As these models continue to mature, the software industry stands on the cusp of a redefined future where human-machine collaboration will shape ground-breaking advancements.

Industry 5.0 is the production model based on the concept of how people and machines can work together. Modern industry is focusing on collaboration between people, robots, and intelligent machines with the help of AI. The design and implementation of solutions, based on Industry 5.0 brings a new level with the latest achievements in Artificial Intelligence and especially the Generative AI, realized on top of the Open AI.
This paper focuses on implementing modern automation with the help of Open AI as a new concept to use AI as a SaaS, integrated with smart machines and robots, helping them to work in a human-like way. The research overviews the use cases and proposes a framework to build a smart solution based on Generative AI and cognitive robots, where integration between SaaS AI and smart machines is based on Cognitive Digital Twins. Research results also include prototypes of cognitive digital twins and its integration with intelligent machines.